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Machine Learning Qa Engineer Jobs (NOW HIRING)

ARBITERSPORTS LLC

Quality Assurance Engineer

Sandy, UT · On-site

We are seeking a curious, analytical, and continuously learning Quality Assurance Engineer. In this role, you will leverage AI powered tools to contribute throughout the development lifecycle ...

Arbitersports

Quality Assurance Engineer

We are seeking a curious, analytical, and continuously learning Quality Assurance Engineer. In this role, you will leverage AI powered tools to contribute throughout the development lifecycle ...

Alliance Industries

QA Engineer

Marietta, OH · On-site

$60 - $80/hr

Technical Marietta, OH, US 3 days ago Requisition ID: 1572 TERRA SONIC - Quality Assurance Engineer ... They work side by side with machinists, fabricators, assembly personnel, and Manufacturing ...

Brilent

QA Engineer Intern

San Mateo, CA · On-site

The Brilent team brings together deep experience in machine learning, and data science from leading ... As a QA Engineer Intern, you will work alongside our small team of engineers to develop new ...

Cinder LLC

QA Engineer

Sunnyvale, CA · On-site

$60/hr

Title: QA Engineer Pay Rate: $60/hr Location: Sunnyvale, CA Type: Fulltime with benefits About ... Experience working in UNIX/Linux environments and using virtual machines. * Knowledge of operating ...

Richmond National

Sr. QA Engineer (Data)

Glen Allen, VA · On-site

$95K - $115K/yr

Job Title: Sr. QA Engineer (Data) Location: On-site in Glen Allen, VA As a QA Engineer (Data) for ... Machine Learning models etc.) through effective testing and automation. You will collaborate ...

Komatsu

Quality Assurance Engineer

Peoria, IL · On-site

$76K - $95K/yr

Review and analyze all TSI and ETSI submitted in Peoria manufactured machines. Organize the data ... Employee learning and development programs Diversity & Inclusion Commitment At Komatsu, we come ...

Curtiss-Wright

Quality Assurance Engineer

Cincinnati, OH · On-site

$75K - $90K/yr

Quality Assurance Engineer We are looking for a Quality Assurance Engineer to join our Cincinnati ... Learning and Development Opportunities I Referral Program I Competitive Pay I Recognition I ...

Victaulic

Quality Assurance Engineer

Easton, PA

We foster an environment for constant learning. * We engineer change for a more stable and sustainable world. YOUR IMPACT STARTS HERE We're looking for a Quality Assurance Engineer to join our Global ...

Enersul Limited Partnership

$80 - $100/hr

## Quality Assurance Engineer\Sr. Quality Assurance EngineerApplylocations: Charlottesville, VAtime ... We're committed to making a positive impact on the world, providing you with diverse learning and ...

Amicis Global

QA Engineer

Seattle, WA · On-site

Title: Web Quality Assurance Engineer (Multiple Positions) Location: Seattle, WA (Onsite) Duration: 6+ Months Key job responsibilities * You'll build and maintain test infrastructure for a web ...

Victaulic

Quality Assurance Engineer

Easton, PA · On-site

We foster an environment for constant learning. * We engineer change for a more stable and sustainable world. YOUR IMPACT STARTS HERE We're looking for a Quality Assurance Engineer to join our Global ...

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All JobsMachine Learning Qa Engineer Jobs

Machine Learning Qa Engineer information

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How much do machine learning qa engineer jobs pay per hour?

As of Sep 9, 2026, the average hourly pay for machine learning qa engineer in the United States is $48.54, according to ZipRecruiter salary data. Most workers in this role earn between $38.22 and $55.53 per hour, depending on experience, location, and employer.

What is a machine learning QA engineer?

Machine Learning QA Engineers are professionals who specialize in testing and validating machine learning models and systems. They ensure that machine learning algorithms perform as expected, are reliable, and meet quality standards before deployment. Their role involves developing test cases, automating testing processes, analyzing results, and collaborating with data scientists and software engineers to improve model accuracy and robustness. They also help identify biases, data inconsistencies, and potential issues in the machine learning pipeline.

What are some common challenges faced by machine learning QA engineers when testing AI models, and how are they typically addressed?

Machine Learning QA Engineers often encounter challenges such as ensuring model accuracy across diverse datasets, reproducibility of test results, and validating the fairness and bias of AI outputs. Addressing these issues typically involves developing robust automated test frameworks, collaborating closely with data scientists to understand model behaviors, and implementing rigorous data validation and monitoring processes. Additionally, continuous learning is essential, as ML models evolve rapidly and require QA Engineers to stay updated on new testing methodologies and tools.

What are the key skills and qualifications needed to thrive as a machine learning QA engineer, and why are they important?

To thrive as a Machine Learning QA Engineer, you need a strong grasp of software testing principles, machine learning concepts, and proficiency in programming languages like Python, along with a relevant degree in computer science or engineering. Familiarity with testing frameworks (such as pytest), ML platforms (like TensorFlow or PyTorch), and experience with automated testing tools are typically required. Exceptional analytical thinking, attention to detail, and effective communication skills set standout candidates apart in this role. These skills and qualities are crucial to ensure the quality, reliability, and fairness of machine learning models before they are deployed to production.

What is the difference between Machine Learning Qa Engineer vs Data Scientist?

AspectMachine Learning Qa EngineerData Scientist
Required CredentialsBachelor's in CS, QA certifications, knowledge of ML modelsBachelor's/Master's in CS, statistics, data analysis
Work EnvironmentTesting labs, development teams, QA departmentsResearch, data analysis, modeling teams
Industry UsageTech companies, AI startups, software firmsTech, finance, healthcare, research institutions
Common Search/ComparisonYesYes

While both roles involve working with machine learning, a Machine Learning Qa Engineer primarily focuses on testing and validating ML models to ensure quality and performance. In contrast, a Data Scientist analyzes data, develops models, and derives insights. The roles often collaborate but serve different stages of the ML development lifecycle.

Is a machine learning QA engineer still in demand?

Machine Learning QA engineers are in demand due to the increasing adoption of AI and machine learning systems across industries. They play a critical role in testing and validating models, often requiring skills in programming, data analysis, and familiarity with tools like Python and TensorFlow. As AI integration grows, the need for specialized QA engineers in this field is expected to remain strong.
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Machine Learning Qa Engineer jobs near you
Infographic showing various Machine Learning Qa Engineer job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 74% Full Time, 23% Part Time, and 1% Contract. Highlights an 83% Physical, 2% Hybrid, and 15% Remote job distribution, with an average salary of $100,970 per year, or $48.5 per hour.

Quality Assurance Engineer

Sandy, UT • On-site

ARBITERSPORTS LLC
Software Development • 51 - 200 employees
Learn more about ARBITERSPORTS LLCexternal

Full-time

Posted 19 days ago

Key responsibilities

  • Participate in refinement and planning sessions to identify risks, gaps, and edge cases, and analyze workflows to determine testing priorities and approach.

  • Create, maintain, and execute test plans, strategies, cases, and automation scripts, and validate functionality across software and hardware solutions using AI tools.

  • Investigate defects through root cause and data analysis, track resolution, and communicate quality risks and testing estimates.

Job description

Description:

We are seeking a curious, analytical, and continuously learning Quality Assurance Engineer. In this role, you will leverage AI powered tools to contribute throughout the development lifecycle, engaging in refinements, challenging requirements, and validating complex, data-driven scenarios. 


You will treat AI as a force multiplier, using it to improve testing efficiency, automation, and analysis, while applying the critical thinking and human judgment needed to validate AI outputs and deliver consistently high-quality software.   


  Essential Job Functions 

  • Participate in refinement and planning sessions to identify risks, gaps, and edge cases early, and analyze system and data workflows to determine testing priorities and approach. 
  • Using AI tools to accelerate testing and analysis; create, maintain, and execute test plans, strategies, cases, and automation scripts; validate functionality across software and hardware solutions.  
  • Critically evaluate, validate, and refine AI-generated outputs to ensure accuracy, completeness, and business relevance. 
  • Perform functional, integration, regression, exploratory, and data-focused testing across applications and services. 
  • Test REST and SOAP APIs, validating JSON and XML responses. 
  • Investigate defects through root cause and data analysis, track resolution, and communicate quality risks and testing estimates, in collaboration with Product, Engineering, and Support stakeholders.  
  • Document test scenarios, results, and findings clearly and concisely. 
  • Contribute to improvement initiatives by identifying opportunities to enhance quality, efficiency, and AI-enabled workflows.  
  • Participate in agile ceremonies including standups, retrospectives, planning, and refinement activities. 
Requirements:
  • Strong ability to analyze data, workflows, and system interactions, and to challenge requirements to clarify business rules and acceptance criteria.  
  • Strong test planning, risk analysis, test design, and execution skills.  
  • Experience automating tests for web-based and distributed systems using Playwright, Selenium, or similar frameworks, within standard development environments (e.g., VS Code, IntelliJ). 
  • Experience testing REST and SOAP APIs using tools such as Postman, SOAPUI, or equivalent platforms. 
  • Experience using AI-powered tools – understanding their strengths, limitations, and risks – to support testing, automation, debugging, analysis, and documentation, and to identify opportunities that improve efficiency and quality. 
  • Strong critical thinking and engineering judgment to prompt, validate, and refine AI-generated outputs. 
  • Highly organized, self-directed, and able to manage multiple priorities in a fast-paced environment.  
  • Excellent written and verbal communication skills. 
  • A collaborative, proactive mindset. 
  • 3+ years of QA or Quality Engineering experience in an agile development environment. 
  • Cellphone or personal device to receive MFA (multi-factor authentication) texts or calls.
  • Have an internet connection that’s adequate for their job, a minimum of 10Mbps down.


 AI Usage & Candidate Authenticity: 


AI tools may be used for resume formatting or drafting application materials; however, submitting content that misrepresents your experience, including copied job descriptions or unverifiable work history, is not acceptable. Candidates must be prepared to clearly and confidently speak to all experience listed. Arbiter may request work samples, portfolio links, or other forms of validation during the process. Use of AI tools during interviews or assessments, unless explicitly permitted, will result in disqualification.  All offers are contingent upon successful completion of a pre-employment background check, including employment and education verification. 

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